Data Engineer designing and building data pipelines at LexisNexis. Collaborating with partners for high - quality analytics and AI - ready data.
About the role
- Senior Azure Data Engineer responsible for data solutions in Data & Analytics team. Requires expertise in Databricks, Azure services, and data pipeline optimization.
Responsibilities
- Design, build, and maintain scalable data solutions that meet business requirements and align with industry best practices.
- Collaborate with the Data & Analytics team on various projects.
Requirements
- 6+ years of experience as a Databricks & Data Engineer, building Azure-based data solutions using Data Factory, Synapse, Databricks.
- Expertise in Python, SQL (SparkSQL, TSQL, PLSQL), Dimensional Data Modeling, Data Warehousing, and ETL/ELT processes.
- Develop and optimize large-scale data pipelines using Databricks, Synapse, and Apache Spark.
- Integrate data into Azure Data Lake Storage via Data Factory and Data Flows.
- Architect Delta Lake & Lakehouse solutions for scalable analytics.
- Optimize performance across Databricks, and Synapse environments.
- Any ERP experience
- Leverage Microsoft Fabric for seamless data integration & transformation.
- Operationalize ML models in Databricks and automate CI/CD pipelines with Azure DevOps.
- Ensure data governance & security with Azure Purview & Databricks Unity Catalog
Job title
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Degree requirement
Tech skills
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